In order for microphones (e.g., installed on portable user devices, such as cellular phones) to be capable of determining their own locations (e.g., relative to one another and to one or more sources of sound) it is necessary to have a set of acoustic events. In an existing approach to self-localization of microphones, acoustic events are created independently of the devices, for example, by a user clapping hands. Such an approach introduces four unknowns per acoustic event (the three spatial coordinates and the time of the event). As the problem of computing the unknowns is highly non-linear, it is difficult to deal with all of these additional unknowns. In particular, the unknown event timing of the acoustic events prolongs the convergence of existing self-localization algorithms.